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Weak maneuvering target detection in random pulse repetition interval radar

机译:随机脉冲重复间隔雷达中的弱机动目标检测

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摘要

The range migration (RM) and Doppler frequency migration (DFM) are the two major problems faced by radar maneuvering target detection. Unlike the existing algorithms which focus on the correction of RM and DFM in the fixed pulse repetition interval (PRI) system, this paper proposes a novel method which can further realize coherent integration in the random PRI system. The proposed method firstly conducts the multi-dimensional search for the maneuvering target's trajectory, then compensates DFM and realizes coherent integration via the nonuniform polynomial sparse Fourier transform (NUPSFT). As a linear algorithm, the proposed method can detect multiple weak targets without generating any cross term. Moreover, a high processing efficiency can be obtained thanks to the application of sparse Fourier transform (SFT). Both theoretical analysis and simulation results have validated the effectiveness of the proposed method.
机译:范围迁移(RM)和多普勒频率迁移(DFM)是雷达机动目标检测所面临的两个主要问题。与在固定脉冲重复间隔(PRI)系统中专注于RM和DFM的校正的现有算法不同,本文提出了一种新的方法,可以进一步实现随机PRI系统中的相干积分。该方法首先对机动目标的轨迹进行多维搜索,然后通过非均匀多项式稀疏傅立叶变换(NUPSFT)来补偿DFM并实现相干积分。作为线性算法,所提出的方法可以检测多个弱目标而不产生任何横向术语。此外,由于稀疏傅立叶变换(SFT)的应用,可以获得高处理效率。理论分析和仿真结果都验证了该方法的有效性。

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